promoting effective schooling through education decentralization in bangladesh, indonesia, and...

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ECONOMICS AND RESEARCH DEPARTMENT

ERD WORKING PAPER SERIES NO. 23

Jere R. BehrmanAnil B. DeolalikarLee-Ying Soon

September 2002

Asian Development Bank

Promoting Effective

Schooling through Educatio

Decentralization

in Bangladesh, Indonesia,

and Philippines


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ERD Working Paper No. 23

PROMOTING EFFECTIVE SCHOOLING

THROUGH EDUCATION DECENTRALIZATION

IN BANGLADESH, INDONESIA, AND PHILIPPINES

Jere R. BehrmanAnil B. Deolalikar

Lee-Ying Soon

September 2002

Jere R. Behrman is William R. Kenan, Jr. Professor of Economics and Director of the Population Studies

Center, University of Pennsylvania. Anil B. Deolalikar is Professor of Economics and Director of South Asia

Center, University of Washington. Lee-Ying Soon is Associate Professor of Economics, Nanyang TechnologicalUniversity, Singapore. The authors are international consultants for TA 5617-REG: Financing Human

Resource Development in Asia. The authors thank Rana Hasan, Shew-Huei Kuo, and her colleagues at the

Asian Development Bank (ADB) for useful comments during the course of the project. The authors alone,

and not ADB, are responsible for the content of this paper.


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CONCEPTUAL ISSUESINTHE ROLEOF EDUCATION DECENTRALIZATION

2

Asian Development Bank

P.O. Box 789

0980 Manila

Philippines

2002 by Asian Development Bank

September 2002

ISSN 1655-5252

The views expressed in this paper

are those of the author(s) and do not

necessarily reflect the views or policies

of the Asian Development Bank.


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Foreword

The ERD Working Paper Series is a forum for ongoing and recently

completed research and policy studies undertaken in the Asian Development Bank

or on its behalf. The Series is a quick-disseminating, informal publication meant

to stimulate discussion and elicit feedback. Papers published under this Series

could subsequently be revised for publication as articles in professional journals

or chapters in books.


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Contents

INTRODUCTION 1

I. Education in Bangladesh, Indonesia,and Philippines in Perspective 2

A. Population and Level of Economic Development 2B. Aggregate Aspects of Schooling 5C. Distribution of Education 11

II. Bangladesh 13

A. Structure of Education 14B. Access to Schooling 14C. Quality of Education 15D. Management of the Education Sector 16E. Financing 17F. The Case for Decentralization of the

Education Sector 18G. Assessing the Impact of Decentralization

in Bangladesh 20H. Implications 25

III. Indonesia 26

A. Structure of Education 26B. Access to Schooling 27C. Quality of Schooling 28D. Management and Budgeting 29E. Financing 30F. School-Based Management and the New

Decentralization Laws 33G. Private Schools and Decentralization 34

H. Implications 37


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PROMOTING EFFECTIVE SCHOOLINGTHROUGH EDUCATION DECENTRALIZATION

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IV. The Philippines 38

A. Structure of Education 38B. Access to Schooling 39

C. Quality of Education 39D. Management and Budgeting 40E. Financing of Education 41F. Decentralization Efforts 43G. Fiscal Decentralization and School Outcomes 44H. Conclusions 49

V. Conclusions 50

Appendix Tables 53

References 56


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CONCEPTUAL ISSUESINTHE ROLEOF EDUCATION DECENTRALIZATION

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Abstract

Among developing member countries (DMCs), Indonesia and the

Philippines rank fairly high in the distribution of real GDP per capita in PPP

dollars while Bangladesh ranks much lower. In terms of aggregate schooling,

the Philippines has secondary and tertiary enrollment rates that are substantially

higher, while Indonesia has rates that are substantially lower, than that predicted

based on all DMCs and their respective real products per capita. The Philippines

also has expected grades for synthetic cohorts that are substantially above the

overall mean for DMCs. In terms of public expenditures on education, all three

countries have about the same percentage of GNP invested in education, a little

over 2 percent, which is significantly below the level predicted by the experience

of all DMCs given their respective real products per capita. There has been

considerable public pressure for decentralization of education in DMCs in recent

years. This pressure has been driven largely by fiscal constraints but has also

been motivated by concerns over the effectiveness of a centralized system for

delivering education services. The three country studies provide a rich

characterization of the evolvingand in certain respects, rapidly changing

education systems in these DMCs.


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INTRODUCTION

This is the second of three Economics and Research Department working papers on the

Asian Development Bank (ADB) project The Role of Education Decentralization in

Promoting Effective Schooling in Selected DMCs. The selected developing member countries

(DMCs) are Bangladesh, Indonesia, and Philippines. It covers part of Phase Two of a larger ADB

project (RETA 5617) whose Phase One addressed the issue of Financing Human Resource

Development in Asia.

As part of the project, consultants from the three DMCs, working with ADB staff andinternational consultants, undertook three country studies. Their tasks were to gather secondary

data and information, to include conducting purposive surveys if necessary, and to prepare a country

report. This working paper is a synopsis of the three country reports.

The three DMCs selected for the project differ significantly in the progress made in the

education sector. The Philippines, for instance, has long had high levels of education compared

with other DMCs at the same level of per capita income. For Bangladesh, in contrast, universal

primary schooling remains elusive, despite substantial progress. In Indonesia, access to primary

schooling was by the mid-1980s no longer an issue and priority had shifted to expanding universal

schooling up to junior secondary level. However, the 1997 financial crisis and subsequent events

have raised concerns that some of the gains in education may be reversed. In all three countries,

the low quality of schooling is acknowledged as critical and has been given priority. In all three

countries decentralization, or further decentralization, is expected to shape policies in the education

sector in the years ahead.

In the three DMCs, the quality of education has been cause for serious concern. Among

measures undertaken to alleviate this state of affairs, as well as maximize the impact of scarce

fiscal resources on overall development objectives, has been the decentralization of government

functions in the education sector. Such decentralization is at various stages of completion. This

working paper presents summaries of the three country studies that have been conducted on the

impact of decentralization on the education sector. Section I begins by providing perspectives

concerning the overall level of economic development and aggregate aspects of education and the

distribution of education in the three countries in the context of all DMCs. Section II summarizesthe Bangladesh study, Section III the Indonesia study, and Section IV the Philippines study. Details

are contained in the complete reports in Masum (2000), Triaswati (2000), and Manasan (2002),

respectively. Section V presents some conclusions.


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This working paper follows on from the conceptual (background) paper for the three country

studies, which identified issues in education and the role that decentralization plays (Behrman

et al. 2002). A full version of the Philippines country report (Manasan 2002) is to be published

as ERD Working Paper No. 24.

I. EDUCATION IN BANGLADESH, INDONESIA,

AND PHILIPPINES IN PERSPECTIVE

In the late 1990s, ADB undertook detailed studies of education trends and patterns in

its DMCs. This section summarizes some of the basic points about the current level of development,

aggregate education activities, and the distribution of education in the three DMCs selected for

the present studyBangladesh, Indonesia, and Philippinesbased on data presented in two ADB

studies (Bray 1998, Lee 1998). These data are subject to definite limitations because different

countries do not use the same definitions and because some important concepts, for instance thoserelated to quality of education, are very poorly measured or not measured at all.1 Nevertheless,

they provide some perspectives about economic development and education in these three countries.

A. Population and Level of Economic Development

Table 1 and Figure 1 present basic population and development statistics for the three

project DMCs and, for comparison, basic summary statistics for all DMCs for which these data

are available (Appendix Table A1 gives the individual country data). For each of four variables

namely, population, GNP per capita (in dollars at official exchange rates), GDP per capita (in

purchasing power parity [PPP] dollars), and the Human Development Index (HDI)a striking

feature is the considerable variance among DMCs. The distribution of each of these four variables

across the DMCs is now summarized, with emphasis on where in this distribution the three project

DMCs are located.

1 These issues in using such data are discussed, for example, in a special symposium in theJournal of DevelopmentEconomics. See Srinivasan (1994) for an overview.


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Table 1. Basic Population and Development Statistics for Project Developing MemberCountries and Summary Statistics for All Developing Member Countries

Population GNP per Capita Real GDP per HumanCountry (million) ($) Capita (PPP $) Development Index

Bangladesh 116.5 220 1,331 0.368Indonesia 194.5 880 3,740 0.668Philippines 66.4 950 2,681 0.672

All Developing Member CountriesMean 82.0 3,007 4,381 0.61Median 9.8 950 2,461 0.63Standard Deviation 243.5 5,483 5,423 0.18Range .0071,208.3 20022,500 75022,310 0.340.91Number of Countries 37 34 28 27

Sources: Calculated from Appendix Table A1. Original sources for country data are UNDP (1997) and various national sourcesas presented in Bray (1998, Table 1). Data refer to the most recent year available to Bray (1998).

1. Population

The range of population is enormous, from 7,000 in Nauru to 1.2 million in the Peoples

Republic of China (PRC). The mean population is 82 million, but the distribution is weighted toward

Section IEducation in Bangladesh, Indonesia, and Philippines in Perspective

Figure 1. Basic Characteristics of the Three Sample Countries

Bangladesh Indonesia Philippines

117 195 66220

880 950

1,331

3,740

2,681

368

668 672

HumanDevelopment Index

(x 1,000)

Real GDP percapita (PPP $)

GNP per capita($)

Population(million)

4,000

3,500

3,000

2,500

2,000

1,500

1,000

500

0


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countries with small populations, with 13 countries having fewer than 1 million inhabitants, so

the median population is only 9.8 million. The three project DMCs all are relatively high in the

distribution of DMC populations: Indonesia (third largest population among DMCs), Bangladesh

(fifth), and Philippines (seventh). Together they account for about an eighth of the total population

of the DMCs or over two fifths of the total DMC population outside of the PRC and India.

2. Product per Capita

There are two measures of product per capita: GNP per capita in dollars based on official

exchange rates and GDP per capita in PPP dollars that incorporate differences in price structures

among countries. For both measures the ranges are large: from $200 (Nepal) to $22,500 (Singapore)

for GNP per capita based on official exchange rates and from $750 (Samoa) to $22,310 (Hong Kong,

China) for GDP per capita in PPP dollars. For countries with lower products per capita, the latter

tends to be higher because of the relative cheapness of nontraded products that are intensive in

unskilled labor in such economies, so the range is a little less if PPPs are used. But the patternsacross DMCs are very similar, with the correlation between the two measures equal to 0.97 for

the 27 DMCs for which both measures are available (Appendix Table A1). The three country study

DMCs are below the means for both measures. But the distribution again is relatively concentrated

among lower values in both cases so that the Philippines is at the median and Indonesia only

slightly below the median for the first measure, and both Indonesia and the Philippines are above

the median for the second measure. All three of these countries rank higher in the distribution

of the PPP measure than in the distribution of the exchange rate-based measure (and Indonesia

has higher product per capita than the Philippines for the PPP dollars measure, though the opposite

is the case for the official exchange rate-based indicators). For real GDP per capita in PPP dollars,

among all DMCs, Bangladesh is at the 25th percentile, the Philippines is at the 60th, and Indonesia

is at the 75th. Thus Indonesia and the Philippines (but not Bangladesh) are fairly high in the

distribution of real product per capita among DMCs, though far below Fiji Islands; Hong Kong,

China; Republic of Korea (hereafter Korea); Malaysia; Singapore; and Thailand.2

3. Human Development Index

The HDI, proposed by the United Nations Development Programme (UNDP), is a frequently

used alternative to product/income per capita measure of development, which, while it includes

income per capita (with a declining weight as income per capita increases), gives equal weight

to direct human resource measures, including schooling. The HDI ranges from 0.34 (Bhutan) to

2 And probably far below Taipei,China for which PPP dollar estimates are not available.


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0.91 (Hong Kong, China) among the 27 DMCs for which the index is available. The HDI varies

much less among DMCs than do the product per capita indicators.3 The HDI is positively correlated

with the two product per capita measures, which is not surprising because one of the components

used to make this index is income/product per capita and the other components are positively

correlated with per capita income; the correlation with GNP per capita using exchange rates for

the 26 countries that have observations on both is 0.61 and the correlation with GDP per capita

using PPP dollars for the 27 countries that have observations on both is 0.74.4 That these correlations

are significantly less than one, however, reflects the fact that the HDI is measuring something

different than per capita product. Among the 27 DMCs, Bangladesh is at the 15th percentile,

Indonesia is at the 67th, and the Philippines is at the 70th. The HDI suggests, thus, similar rankings

of the three project DMCs among all DMCs as do the income/product per capita measures (though

with some slight shifts, such as between the Philippines and Indonesia).

B. Aggregate Aspects of Schooling

Table 2 presents basic aggregate statistics on selected aspects of schooling for the three

project DMCs and, for comparison, basic summary statistics for all DMCs for which these data

are available (Appendix Tables A1 and A2 give the individual country data). The summary statistics

for all DMCs include the mean, median, standard deviation, and range (first column), and the

consistency (R2 adjusted for degrees of freedom, which indicates how much of the variance in each

variable is consistent with the variance in real GDP per capita) of each variable with real GDP

per capita in PPP dollars among the DMCs for which data are available (last column). For the

three project DMCs, for each variable the top entry is the actual value of the variable for that

country and the bottom entry is the value predicted on the basis of a regression for all DMCs

and the real GDP per capita in PPP dollars for that country (with the percentage discrepancy

between the actual and the predicted values relative to the actual value in parentheses). 5 The

3 The coefficient of variation (i.e., the ratio of the variance to the mean) is 0.053 for the HDI, $6,713 for GDPper capita in PPP dollars, and $9,998 for GNP per capita at real exchange rates.

4 The differences between these two correlations reflect that controlling for prices better leads to a higher correlationbetween income/product per capita than that obtained with real exchange rate GNP per capita.

5 For example, the first row indicates that for preprimary enrollment rates for all 17 DMCs for which data areavailable, the mean is 31.5 percent, the median 23.0 percent, and the standard deviation is 28.1 percent, andthat a regression of preprimary enrollment rates on the real GDP per capita in PPP dollars among the DMCs

for which data are available is consistent with about half (0.498) of the variation in preprimary enrollmentrates for these DMCs. For Bangladesh, no data are available on preprimary enrollment rates, but the predictedvalue based on Bangladeshs real GDP per capita in PPP dollars is 19 percent. For Indonesia, the actualpreprimary enrollment rate is 19 percent and the predicted value based on its real GDP per capita in PPPdollars is 28 percent, so the difference between the actual and the predicted value is negative and equal to49 percent of the actual value.



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Table 2. Summary Statistics for Aggregate Schooling Indicators for all DMCsand Actual and Predicted Values and Percent Discrepancy for Three DMCs

Mean, Median (standard Project Country (actual values anddeviation), and Range predicted values and percent discrepancy

for all Developing between actual and predicted)b

R2

/Nc

Variable Member Countriesa

Bangladesh Indonesia Philippines

Gross Enrollment Rates, 1995 (%)Preprimary 31.5, 23.0 (28.1) 19 13 0.498

190 19 28 (-49%) 24.1 (-85%) 17

Primary 101.8, 103.0 (17.9) 114 116 0.018d

49134 108 103 (10%) 104 (10%) 27

Secondary 54.3, 52.0 (25.3) 48 79 0.092d

14101 46 58 (-21%) 54 (25%) 26

Tertiary 15.3, 10.9 (13.9) 11.1 27.4 0.333d

1.552 7.1 16.5 (-49%) 13.5 (51%) 20

Expected Grades of Schooling 9.6, 9.4 (1.8) 9.7 12.0 0.008dfor a Synthetic Cohorte 5.613.2 9.2 9.8 (-1%) 9.6 (20%) 19

Public Expenditures on 3.9, 4.0 (1.5) 2.3 2.2 2.2 0.000d

Education as % of GNP 1.06.8 3.4 (-48%) 3.7 (-67%) 3.6 (-63%) 23

Public Expenditures on 14.9, 17.0 (4.5) 8.7 0.221d

Education as % of Total 7.423.1 12.2 (-40%) 15.0 14.1 19Government Budget

Percent Distribution of Recurrent Expenditures, 1992Primary 45.2, 43.5 (9.5) 44.2 63.9 0.149

26.963.9 48.2 (-9%) 46.3 47.1 (26%) 17

Secondary 29.3, 29.1 (9.9) 43.3 10.1 0.130d

10.143.5 26.1 (40%) 30.8 29.3 (-190%) 17

Tertiary 14.7, 14.7 (7.9) 7.9 22.5 0.0293.230.0 13.7 (-73%) 14.3 14.3 (37%) 17

Private Enrollment as Percent of Total EnrollmentPreprimary 56.9, 53.0 (40.8) 100 53 0.057d

0100 38 57 (43%) 51 (5%) 15

Primary 10.7, 4.0 (21.1) 18 7 0.000d

096 6.9 12.9 (28%) 11.0 (-57%) 20

Secondary 23.4, 6.0 (28.8) 42 35 0.000d

087 14.6 18.2 (57%) 17.0 (51%) 21

means not available.

Notes: Calculated from data in Appendix Tables A1 and A2. Data refer to the most recent year available to Bray (1998), in most cases the mid-1990s.

a These summary statistics are for all the DMCs for which the data are available in Appendix Table A1, with the number for each row indicated

in the last column. The standard deviation is in parentheses.b The first item in each cell for the three DMC project countries is the value reported in Appendix Table A1. Beneath the actual data is the value

predicted by a regression on the real GDP per capita in PPP terms for all DMCs for which data are available for that variable (see last columnfor some details of the regressions).

c This column gives the adjusted R2 for the regression among all DMCs for which data are available for the regression used to predict the valuesfor the three project countries conditional on their respective real GDP per capita in PPP terms and the number of observations used in theregressions. The underlying relation is linear or semilog (the latter indicated by d) depending on which is more consistent with the variance inthe variable being predicted.

d The right-side real GDP per capita PPP variable is in ln terms so that the relation is in semilog form.e The expected grades of schooling for a synthetic cohort is the number of grades of schooling that would be expected for individuals with the

reported enrollment rates for the three schooling levels, assuming that there are six grades in the primary level, five in the secondary leveland four in the tertiary level.


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distribution of each of these variables across DMCs is now summarized, with emphasis on where

in this distribution the three project DMCs are located.

1. Gross Enrollment Rates for Different Schooling Levels

The ranges of gross enrollment rates are considerable for all four schooling levels: 1-90

percent for preprimary, 49-134 percent for primary, 14-101 percent for secondary, and 1.5-52 percent

for tertiary school.6 The means for all DMC gross enrollment rates are 31.5 percent for preprimary,

101.8 percent for primary, 54.3 percent for secondary, and 15.3 percent for tertiary school. Thus

there is an inverted U with the highest enrollment rates for primary school, followed by secondary

school. The medians are quite similar for primary and secondary school, but are substantially

lower for preprimary and tertiary schoolimplying that for the latter two levels the distributions

are skewed relatively to the right due to some very high enrollment DMCs (namely Hong Kong,

China, with 90 percent and Korea with 85 percent for preprimary, and Korea at 52 percent for

tertiary). For the preprimary level the variation across countries is relatively large while for theprimary level it is relatively small, with the secondary and tertiary levels in between. 7 The

preprimary and tertiary enrollment rates (more so the former) are fairly strongly associated with

per capita income, but the primary and secondary enrollment rates much less so.

Both Indonesia and the Philippines have the same general inverted U pattern of enrollment

rates across schooling levels as occurs on average across all DMCs, and both have primary

enrollment rates 10 percent above the predictions based on the experience of all DMCs (there

are no data for Bangladesh). But there are some differences from the experience of all DMCs in

the details of the experiences of these two countries. Both (particularly the Philippines) have

relatively low preprimary enrollment rates, substantially below what would be predicted on the

basis of all DMCs (with discrepancies of -49 and -85 percent of the actual rates). These relatively

low preprimary enrollment rates raise the question of whether children in these two countries

are disadvantaged in comparison with other DMCs when they enter primary school. Indonesia

also has secondary and tertiary enrollment rates that are substantially below the predictions based

on all DMCs (with discrepancies of -21 and -49 percent of the actual rates). In contrast, the

Philippines has secondary and tertiary enrollment rates that are substantially above the predictions

based on all DMCs (with discrepancies of 25 and 51 percent of the actual rates). If schooling at

the secondary and tertiary levels is likely to become more important in dealing with market and

6 The gross enrollment rates give reported enrollment as a percentage of the population in the normal age rangefor that school level. They may exceed 100 percent if there are students who are younger or older than thosein the normal age range for that school level.

7 The coefficients of variation for the four levels are 25.1, 3.1, 11.8, and 12.6.



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technological changes, as some experts predict, the Philippines would seem to be much better

positioned than Indonesia.8

2. Expected Grades of Schooling for a Synthetic Cohort

This is a summary measure of the enrollment rates and is calculated by asking how many

grades of schooling would a cohort of students get if the enrollment rates are those that are currently

experienced (not including preprimary schooling). The range of expected grades of schooling among

DMCs is considerable, from 5.6 for Papua New Guinea to 13.2 for Korea, though there is not a

significant association with per capita income. The mean and median are about the same at 9.6

and 9.4 grades, respectively. The expected grades of schooling for a synthetic cohort in Indonesia

is 9.7, at about the overall mean for DMCs and at about the predicted level for the country based

on the overall experience of DMCs. In sharp contrast, the expected grades of schooling for a synthetic

cohort in the Philippines is 12.0, substantially above the overall mean for DMCs and substantially

above the predicted level for the country based on the overall experience of DMCs. This way ofsummarizing the enrollment rates thus again emphasizes the considerable difference between

the extent of schooling investments in the Philippines and Indonesia.

3. Public Expenditures on Education

Public expenditures on education are an important source of resources for education in

most countries. As a percentage of GNP they vary considerably among DMCs, from 1.0 percent

in Cambodia to 6.8 percent in the Kyrgyz Republic, but without a significant association with per

capita income. The mean and median are about the same at 3.9 and 4.0 percent, respectively.

The three project countries all have about the same percentage of GNP devoted to public

expenditures on education2.3 percent for Bangladesh and 2.2 percent for Indonesia and the

Philippines. These all are considerably below the percentages predicted by the experience of all

DMCs given their respective real products per capitawith discrepancies from -48 to -67 percent.

Such comparisons raise the question of whether sufficient public resources are being expended

on education in the three project DMCs, though the underlying question of more fundamental

interest concerns total resources, whether public or private.

Public expenditures on education as a percentage of total government budgets range from

7.4 percent in Viet Nam to 23.1 percent in the Kyrgyz Republic. The mean for all 19 DMCs for

which data are available is 14.9 percent, somewhat below the median at 17.0 percent, which reflects

8 But it should be noted that the Philippines long has had high schooling in comparison with other DMCs controllingfor per capita income, but that has not led to a better development experience over the past three decades(see Behrman and Schneider 1994).


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the concentration of about a third of the DMCs with data of 1718 percent in combination with

five countries spread out in the lower tail below 12 percent (Viet Nam 7.4, Sri Lanka 8.1, Bangladesh

8.7, Bhutan and Cambodia 10.0 percent). In contrast with public expenditures on education as

a percentage of GNP, these expenditures as a percentage of total government budgets are

significantly positively associated with real product per capita. Thus DMCs with higher per capita

income tend to spend larger shares of their government budgets on education but also tend to

have smaller government shares of total product.9 Information on this variable is available,

unfortunately, only for one of the three project DMCs. Bangladesh is reported to allocate 8.7 percent

of its government budget to education, which is substantially below the 12.2 percent predicted

on the base of the experience of all DMCs, given Bangladeshs GDP per capita in PPP dollars.

This reinforces the question above of whether sufficient public resources are being devoted to

education.

4. Percentage Distribution of Recurrent Expenditures Among

Schooling Levels

These distributions vary considerably among DMCs, from 26.9 percent (Hong Kong, China)

to 63.9 percent (Philippines) for the primary level, from 10.1 percent (Philippines) to 43.5 percent

(Lao Peoples Democratic Republic) for the secondary level, and from 3.2 percent (Vanuatu) to

30.0 percent (Hong Kong, China) for the tertiary level. The means (which are very close to the

medians) for the three levels, respectively, are 45.2, 29.3, and 14.7 percent. There is a weak but

significant tendency for the shares devoted to the primary and secondary levels to increase with

GDP per capita. Bangladesh allocates about equal percentage shares to the primary and secondary

levels (43 and 44 percent, respectively) and a relatively small share to the tertiary level. In

comparison with the shares predicted by the experience of all DMCs, Bangladesh allocates much

more to the secondary level and much less to the tertiary level (as well as a little less to the primary

level). The Philippines allocates the largest share among all DMCs (63.9 percent) to the primary

level, the second largest share (23.5 percent) to the tertiary level, and the smallest share (10.1

percent) to the secondary level. In comparison with the shares predicted by the experience of all

DMCs, the Philippines allocates much more to the primary level and somewhat more to the tertiary

level (and therefore much less to the secondary level).

9 The correlation between the government share in product and real GDP per capita in PPP dollars is -0.26.This reflects that, among the DMCs that have both of these variables, the six largest shares of government

in product are for four relatively low per capita product DMCs (40 percent for Bhutan, 38 percent for Sri Lanka,and 29 percent for India and the Kyrgyz Republic) and two medium per capita product DMCs (34 percent forMalaysia and 29 percent for the Fiji Islands) and the six smallest shares are for three of the four DMCs withthe highest per capita product for which such data are available (16 percent for Hong Kong, China and 21percent for Korea and Thailand) as well as for three DMCs with relatively low product per capita (22 percentfor Nepal, 19 percent for the PRC, and 10 percent for Cambodia).



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These two project DMCs, thus, take very different strategies regarding the allocation of

public resources among the three levels (data are not available for Indonesia). If, as is claimed

by some such as Psacharopoulos (1994), the social rates of return are highest to primary schooling,

the Philippine strategy with high concentration of public expenditures on primary schooling has

efficiency advantages. But the empirical basis for such claims is weak because the underlying

estimates do not include the possibility of social benefits beyond private ones, which some

commentators claim may increase the true social rates of returns relatively for tertiary schooling,

particularly in science and engineering. If the critical bottleneck in the future is likely to be

increasingly at the secondary level as Sussangkarn (1990) has claimed (at least for Thailand),

then from an efficiency perspective Bangladesh may be following the better strategy. From the

point of view of distribution, the Philippines seems to be favoring substantially the poor with

resources to the primary level and the better-off with resources to the tertiary level, presumably

to the disadvantage of those in between whom Bangladesh is favoring. Of course there are other

critical questions that need to be addressed regarding these strategies, including, importantly,

the extent to which private resources are used differentially across school levels. But the differencesin these patterns raise some important questions about resource allocations among school levels

for the project.

5. Private Enrollments as Percentage of Total Enrollments

at Different School Levels

There is considerable variation among DMCs in the shares of private enrollments in total

enrollments for the three school levels for which data are available. The ranges are from 0 to 100

percent for the preprimary level, from 0 to 96 percent for the primary level, and from 0 to 87

percent for the secondary level. The respective means are 56.9, 10.7, and 23.4 percent, suggesting

a V-shaped pattern across these three school levels. The medians for the primary and secondary

levels at 4.0 and 6.0 percent are much lower than the means because for these two school levels

the distributions are concentrated at relatively low percentages with a few outliers with small

populations (e.g., Fiji Islands, joined by Kiribati and Tonga for the secondary level) with quite

high percentages. Both Indonesia and the Philippines also have a V-shaped pattern across these

three school levels (data are not available for Bangladesh). Compared with the private enrollment

rates as percentages of total enrollment rates predicted by the experience of all DMCs, Indonesia

has higher private shares at all three levels. The Philippines has about the predicted percentage

at the preprimary level, a much lower than predicted percentage at the primary level, and a higher

than predicted percentage at the secondary level (with the latter two consistent with the high

share of public resources allocated to the primary level and the low share allocated to the secondarylevel that are noted above). Such differences provide some additional clues about quite different

public-private strategies followed in these two countries.


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C. Distribution of Education

There are a number of aspects of the distribution of education that are of interest. The

distributions by gender, ethnic group, region, urbanization, sociocultural background, income, caste,

tribe, race, and national origin are some common examples. The general patterns (though not

without exceptions) in the DMCs indicate that males, majority ethnic groups, urban residents,

residents of more prosperous areas, and those from higher-income families average more schooling.

An ADB paper by Lee (1998) provides a study of such aspects of distribution in the DMCs.

For most of these aspects of distribution, very few, if any, statistics permit placing the

experience of the three project DMCs within the broader context of all DMCs as above in this

section. One exception pertains to gender.

Table 3 presents basic aggregate statistics on selected aspects of gender and schooling for

the three DMCs of particular interest for this study and, for comparison, basic summary statistics

Table 3. Statistics Related to Gender for Three Project Developing Member Countries andSummary Statistics for All Developing Member Countries

Gender Male to Female Male to Female GrossDevelopment Adult Literacy Enrollment Rates

Developing Member Country Index, 1994 Rates, 1994 Primary 1993 Secondary 1992

Bangladesha 0.34 2.1 1.2 1.90.47 (-39%) 1.6 (23%) 1.2 (0%) 1.5 (24%)

Indonesiaa 0.64 1.2 1.0 1.20.64 (1%) 1.3 (-12%) 1.1 (-10%) 1.3 (-7%)

Philippinesa 0.65 1.0 1.0 0.9b

0.58 (10%) 1.4 (-43%) 1.1 (-13%) 1.4 (-50%)

All Developing Member CountriesMean 0.62 1.5 1.2 1.4Median 0.64 1.2 1.0 1.2Standard Deviation 0.16 0.62 0.26 0.52Range 0.320.85 1.03.2 1.02.0 0.82.8Number of Countries 23 25 22 21R2c 0.731d 0.179d 0.117d 0.155

Sources:Calculated from Appendix Table A3. Original sources for country data are UNDP (1997), UNESCO, and various nationalsources as presented in Lee (1998, Tables 1, 3, 5, and 6).

a The first item in each cell for the three DMC project countries is the value reported in Appendix Table A3. Beneath theactual data is the value predicted by a regression on the real GDP per capita in PPP terms for all DMCs for which data

are available for those variables (see last row for R2

for this regression).b 1980.c This row gives the adjusted R2 for the regression among all DMCs for which data are available for the regression used to

predict the values for the three project countries conditional on their respective real GDP per capita in PPP terms and thenumber of observations used in the regressions. The underlying relation is linear or semilog (the latter indicated by d), dependingon which is more consistent with the variance in the variable being predicted.

d The right-side real GDP per capita PPP variable is in ln terms so that the relation is in semilog form.



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for all DMCs for which these data are available (Appendix Table A3 gives the individual country

data. The table has information that is presented in a manner similar to that in Table 2.) The

summary statistics for all DMCs include the mean, median, standard deviation, and range, and

the consistency (R2 adjusted for degrees of freedom) of each variable with real GDP per capita

in PPP dollars among the DMCs for which data are available. For the three DMCs on which this

study focuses, for each variable the top entry is the actual value of the variable for that country

and the bottom entry is the value predicted on the basis of a regression for all DMCs and the

real GDP per capita in PPP dollars for that country (with the percentage discrepancy between

the actual and the predicted values relative to the actual value in parentheses). The distribution

of each of these variables across the DMCs is now summarized, with emphasis on where in this

distribution the three project DMCs are situated.

The Gender-related Development Index (GDI) uses the same variables as the HDIlife

expectancies, education attainment, and incomebut adjusts the average outcomes for a country

to reflect disparities between females and males in these outcomes (for details see UNDP 1993).

Among the DMCs for which both are available the patterns are almost the same; the adjustedR2 for a regression of GDI on HDI is 0.98. Among the DMCs the GDI ranges from 0.32 (Nepal)

to 0.85 (Singapore), with a fairly strong relation to GDP per capita in PPP dollars (i.e., the adjusted

R2 is 0.73). Bangladesh has a GDI of 0.34, the second lowest among the DMCs for which data

are available and substantially below the value of 0.47 predicted from Bangladeshs GDP per capita

and the experience of all the DMCs. This is in contrast to the other two project countries, Indonesia

and the Philippines, which have GDIs of 0.64/0.65 that are at about or slightly above the mean

and median for all DMCs and at (Indonesia) and above (the Philippines) the values predicted by

the experience of all DMCs conditional on their respective GDPs per capita.

The GDI, as noted, uses education attainment and gender disparities in education

attainments as one of its three major components. Table 3 also includes three variables that are

directly reflective of gender differences in education: the male/female ratios for adult literacy,

for primary school gross enrollment rates, and for secondary school gross enrollment rates. All

three of these indicators are highly correlated among DMCs with the GDI (with correlation

coefficients of 0.81, 0.79, and 0.91). For all three of these indicators at the means for all DMCs,

there historically was (for current adult literacy), or currently is (for current enrollments), more

investment in the education of males than of females (so all the means exceed one). That the mean

of 1.5 for past education (as reflected in literacy for current adults) is greater than the mean of

1.2 for current primary enrollments (which generally will result in literacy) suggests that, on

average, the extent to which males are favored in basic education has been declining among DMCs.

The larger ratio at the means for male/female secondary school enrollments than for primary school

enrollments, however, suggests the persistence of substantially greater investments in male thanin female education beyond the basic level. For each of these three indicators, finally, the medians

are less than the means because the means are increased by a few countries (e.g., Afghanistan,

Pakistan, Nepal, Bhutan) for which investment in male education is much greater than in female

education even though in most DMCs the ratios are close to one. In fact the median (as well as


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the lower end of the range) for the male/female ratio of primary school enrollments is 1.0 and

for five DMCs for secondary enrollments it is less than one (i.e., Cambodia, Malaysia, Micronesia,

Philippines, and Sri Lanka).

The three project DMCs have fairly different indicators of the extent to which investments

in education have been greater in males than in females. For Bangladesh the male/female ratios

of education investments have been the greatest, at 2.1 for adult literacy, 1.2 for gross primary

enrollments, and 1.9 for gross secondary enrollments. The comparison of the first with the second

of these suggests a substantial recent decline in the extent to which investments in basic education

is greater for males than for females, but the third suggests an ongoing large gender differential

beyond basic education. Both for adult literacy and for secondary enrollmentsbut not for primary

enrollmentsthe actual male/female ratios of education investments are greater than predicted

on the basis of the experience of all DMCs and Bangladeshs real GDP per capita. For Indonesia

the male/female ratios of education investments are much smaller than for Bangladesh though

somewhat larger than for the Philippines, with a ratio of 1.2 for adult literacy, 1.0 for gross primary

enrollments, and 1.2 for gross secondary enrollments. The comparison of the first with the secondof these suggests a recent decline in the extent to which investments in basic education is greater

for males than for females, but the third suggests an ongoing gender differential beyond basic

education. For all three of these indicators the actual ratios of male to female education investments

are smaller by 712 percent than predicted on the basis of the experience of all DMCs and

Indonesias real GDP per capita. For the Philippines the male/female ratios of education investments

have been the smallest, not only among the three project countries but among almost all DMCs,

with ratios of 1.0 for adult literacy and for gross primary enrollments and 0.9 (in 1980) for gross

secondary enrollments. The comparison of the first with the second of these suggests no substantial

recent decline in the extent to which investments in basic education differ between males and

females, and the third suggests a gender differential beyond basic education with higher enrollment

rates for females than for males. For all three indicators the actual male/female ratios of education

investments are smaller than predicted on the basis of the experience of all DMCs and the

Philippines real GDP per capita.

II. BANGLADESH10

Bangladesh has made substantial progress in improving access to education, especially

at the primary level. Net enrollments for primary school ages, which stood at less than 50 percent

in 1971, increased to 85 percent in 1999. The quality of education, however, remains extremely

poor as indicated by high dropout rates at the primary level and failure rates of secondary students

10 This section draws on the country report on Bangladesh by Masum (2000).

Section IIBangladesh


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in public examinations at the university level. All indicators point to gross inefficiency and poor

management of the education system. At the same time, public spending on education since 1995

has been on the decline. With the current high rate of growth of enrollments at all levels, unless

resource allocation, both public and private, to the education sector can be significantly increased,

it will be difficult even to maintain the current level of coverage and quality standards. Hence

the major issue for decentralization in Bangladesh is how it can relieve fiscal pressures and mobilize

increased resources for maintaining and improving the coverage and quality of education.

A. Structure of Education

In Bangladesh, primary schooling begins at the age of six, is compulsory and free, and

consists of 5 years (classes IV). Secondary education consists of 3 years of junior secondary

education (classes VIVIII), 2 years of secondary (classes IXX) and 2 years of higher secondary

(classes XIXII). Public examinations are given at the end of Class X, the Secondary School

Certificate (SSC), and at the end of Class XII, the Higher School Certificate (HSC). Results ofthese examinations determine eligibility for transition to the next level. Students who succeed

in passing the SSC examination have the option to join a college for higher secondary education

or to enroll in a technical institute for a technical education. The results of the HSC determine

admission to undergraduate education, of 2 to 4 years, is offered in a number of public and private

universities, degree colleges, technical colleges, and specialized institutions. Postgraduate education,

normally of 1 or 2 years, is provided at universities and selected degree colleges and institutions.

B. Access to Schooling

Substantial progress has been made in expanding primary school enrollments. This is

thought to be largely the result of the passage in 1991 of the Compulsory Primary Education Act

that provided for universal compulsory primary education. The Food for Education Program

introduced in 1993/94 also contributed to higher enrollments and retention of children from poorer

families.11 Primary enrollments increased from 12.6 million in 1991 to 18.4 million in 1998. Most

of the increase was accommodated by increases in enrollments in nongovernment schools, either

in schools initiated by local communities or by nongovernment organizations. The latter play an

important role in providing primary education to underserved populations. Net enrollments stood

at 85 percent (in 1999) with females making up 48 percent of enrollments. Access to primary schools,

however, remains unequally distributed among different socioeconomic groups. The net enrollment

rate for slum children of Dhaka City in the 611-year age group is only around 60 percenta

11 The Program, which provides 15 kilograms of wheat per month to landless poor families for sending their childrento school, covered 17,403 schools in 1998 benefiting 2.3 million students belonging to 2.2 million families.


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level that is even lower than rural enrollment rates. Enrollment rates are also low for very poor

householdsonly about 40 percent of children from such households are enrolled in schools because

of the high opportunity cost of sending children to school.

The marked increase in enrollment and completion rates at the primary level during the

1990s increased the pool of potential enrollees at higher levels and thereby helped raise enrollment

rates at the junior secondary and secondary levels. Enrollments increased from 5.1 million in 1995

to 6.3 million in 1999, an increase of 24 percent. In 1997, 44 percent of the age group 1113 were

enrolled in junior secondary while 27 percent were enrolled in secondary school (World Bank 1999).

In 1995, the corresponding figures were 38 percent for junior secondary and 25 percent for secondary

school (ADB 1998a), all of which clearly points to improvements in access to secondary education.

The improved access to secondary schools is due to the fact that tuition fees are heavily

subsidized by the Government. Tuition fees are nominal in government secondary schools as the

Government virtually bears the full costs. Nongovernment secondary schools are also subsidized

with the Government paying 80 percent of basic salaries, house rent, and medical allowances to

teachers appointed against sanctioned posts of all recognized nongovernment secondary schools.The Government also provides occasional grants for construction and maintenance and for teacher

training at training institutes. The remaining resource needs are met largely from student fees,

but there is also some income from other sources.

However, nonschool costs for uniforms, transport, and especially private tutoring12 (in

addition to tuition fees) add significantly to the cost of schooling, thereby limiting access of children

from poorer families. Another reason for differential enrollments across socioeconomic groups is

differential physical access. Schools, most of them belonging to the private sector, have not been

set up on the basis of any school mapping exercise. Consequently some backward and poorer regions

are not served by any secondary school whereas prosperous regions have experienced a proliferation

of schools. Further, in a country where nearly half the population lives below the poverty line,

the opportunity cost of education in terms of income forgone that could be derived from child labor

is potentially significant. For the last reason, to improve access the Government has intervened

with programs like Food for Education, Primary Education Stipend Project, and Stipend for Girl

Students at secondary schools outside municipal areas.

C. Quality of Education

It is widely perceived that students complete 5 years of primary education with a mastery

of only about 3 years of the content. A study of basic skills among the rural poor shows an even

more distressing realitythat only one third of those who have completed primary school have


12 Private tutoring is heavily relied upon in student preparations for public examinations. Hence, even in theabsence of school fees, income can be a significant determinant of enrollments, especially at the secondarylevel and higher.


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mastered basic skills in reading, writing, and oral and written arithmetic. Every year the top 20

percent of students of Class V of the primary schools sit for the primary scholarship examination.

Of those who sat for the examination in 1995, only 24 percent passed (i.e., with 33 percent or

more correct answers). This implies that only 5 percent of the primary school students in grade

V achieved a minimum recognized level of competence.

Some of the recognized causes of the poor and deteriorating quality of primary education

in Bangladesh are the limited number of contact hours (daily school time of 120 minutes for classes

I and II and 240 minutes for classes III to V), and high and increasing student/teacher ratios because

of the surge in enrollments and the poor motivation of teachers due to their overburdening by

nonacademic and nonschool responsibilities.

There are also indications that the quality of secondary education is low. Failure rates

on the SSC examinations are high.13 Some of the recognized causes of the poor quality of education

at the secondary level are increasing student/teacher ratios due to growth in secondary enrollment,

stringent government regulations relating to sanctioning of teaching posts (for 60 students in a

class a post is sanctioned and a second post is not sanctioned unless the class size reaches 120),inadequate physical facilities, faulty recruitment (recruitment of teachers with expertise having

little relevance to teaching at school level), too few inspections and above all, poor motivation of

teachers.

D. Management of the Education Sector

There are three administrative tiers of government below the central Government. The

country is divided into six divisions, each placed under a Divisional Commissioner; each division

is divided into districts (totaling 64) each headed by a Deputy Commissioner; and each district

is divided into upazilas (totaling 460) each headed by an Upazila Nirbahi Officer and thanas (totaling

36) in metropolitan cities.

The overall responsibility of management of primary education lies with the Primary and

Mass Education Division (PMED). While the PMED is involved in the formulation of policies, the

responsibility for implementation rests with the Directorate of Primary Education (DPE) and its

subordinate offices reaching down to the upazila level. The DPEs responsibilities include

recruitment, posting, and transfer of teachers, arranging for in-service training, distribution of

free textbooks, and supervision of schools. At the school level (both government and nongovernment)

13 Unfortunately the SSC results may be flawed as an indicator of learning achievements of the students at thesecondary level for a number of reasons that include: (i) subvention payments to nongovernment schools dependingon the schools performance in the SSC examination, as a result of which, quite often, a sizable number ofstudents do not take the examination lest they perform poorly; (ii) for the same reason as (i), teachers servingas monitors in examination centers often facilitate and encourage copying by students; and (iii) heavy relianceon private coaching prior to SSC examinations.


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are school management committees (SMCs) formed under government directives with well-defined

functions. The SMC consists of 11 members representing guardians, teachers, donors, and local

elites. There are also parent-teacher associations (PTAs) whose role is to build a favorable teaching

and learning environment in schools.

The responsibility for school construction, repair, and supply of school furniture lies with

the Facilities Department (FD) and Local Government Engineering Department (LGED). The

National Curriculum and Textbook Board (NCTB) is responsible for development of the curriculum

and production of textbooks.

For secondary schools the Ministry of Education (MOE) is responsible for formulation of

policies, while the Directorate of Secondary and Higher Education (DSHE), under the Ministry

of Education, is responsible for implementing the same at the secondary and higher education

levels. The NCTB is responsible for developing curriculum, and publishing standard textbooks.

Six region-based Boards of Intermediate and Secondary Education are responsible for conducting

the two public examinations, SSC and HSC, in addition to granting recognition to nongovernment

secondary schools.In principle, a highly centralized bureaucracy manages government secondary schools, but

in practice schools enjoy some autonomy. Principals have considerable operational freedom within

the school campus. However, the teachers are centrally recruited and posted to individual schools,

and their expertise often fails to match the needs of the schools. Principals have no authority to

take corrective measures; neither can they fill any vacant post and have to wait for some time

before a new recruit or an existing staff member joins on transfer from another school.

Nongovernment secondary schools have SMCs that are formed according to directives of

the Government and are responsible for mobilizing resources, approving budgets, controlling

expenditures, and appointing and disciplining staff. Government secondary schools do not have

SMCs. The principal is responsible solely for running the school and is supervised by the Deputy

Director of the respective district.

In short, the management of both primary and secondary education in Bangladesh is highly

centralized. In the case of primary schools it is through a chain of bureaucratic apparatus reaching

to the upazila level and beyond. At the secondary level, management control is conducted indirectly

through directives in the case of nongovernment schools, and directly, in the case of government

schools. Although SMCs have been formed in all primary and nongovernment secondary schools,

SMCs in primary schools have little to do; SMCs in nongovernment secondary schools are vested

with authority but appear not to be doing enough.

E. Financing

Bangladesh is heavily dependent on external sources of financing for the development

budget. External aid finances more than 50 percent of the development expenditure on education.

Development expenditure on education increased from an average of 0.27 percent of GDP

during 19731980 to 1.06 percent of GDP in 1995, taking total expenditure as a percentage of



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GDP to a peak of 2.4 percent in 1995. However, from that date expenditure on education declined,

to 2.2 percent in 1998, primarily as a result of the fall in development expenditure. Real public

spending per student per annum for primary education declined from Tk570 in 1993/94 to Tk525

in 1995/96, with possible adverse effects on the quality of education.

Teacher salaries in government primary schools and grants for salary subvention for

nongovernment primary schools together accounted for 96.7 percent of total current spending on

primary education in 1998, with operation and maintenance accounting for only 3.3 percent. Very

little if anything is left for spending on other pedagogical inputs. Development expenditures in

primary education are spent largely on building, renovating, and improving physical facilities.

At the secondary level, 79 percent of expenditures go toward teacher subvention payments

to nongovernment secondary schools while grants from the development budget are primarily for

construction.

F. The Case for Decentralization of the Education Sector

Despite considerable investment of scarce resources in the education sector, the quality

of education in Bangladesh has probably deteriorated. A decentralized, well-functioning education

system with a proper balance of resources and authority at the school level that is accountable

to the communities might result in a better allocation of resources and contribute to improvement

in the quality of education. This is the most forceful argument in favor of decentralization of

education in Bangladesh.

Moreover, the resource needs for the education sector are fast expanding due to higher

enrollment rates at all levels of education. In the face of the decline in the share of public expenditure

on education, and the high level of dependence on donor funding for development expenditures,

there is virtually no other option but to seek greater community support. This can be expected

only if the education system is properly decentralized and made accountable to the community

it serves.

1. Decentralization Efforts

Before the arrival of the British, Bangladesh had a highly decentralized system of education.

Under British rule, Woods Education Dispatch of 1854 accepted the principle that mass education

was a state responsibility. Departments of Education were set up in all the provinces. Strict school

discipline was enforced through an intensive system of inspection that also ensured that the

Government determined the curriculum that was adopted, and that relevant government rules

and regulations were complied with. The process of centralization thus began. After independencein 1947, the Government of the new state of Pakistan, facing the challenge of national integration,

decided to retain its firm centralized control in the education sector. State control on education

was perpetuated after Bangladesh gained independence from Pakistani rule in 1971. The

constitution of Bangladesh adopted four fundamental state principlesnamely, nationalism,


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democracy, socialism, and secularismfor achieving the objectives of the state. Control over the

education sector was further tightened in pursuit of these principles, culminating in the

nationalization of primary education in 1973.

In 1983, the Government adopted a policy of administrative decentralization. Services of

various functionaries of the central Government including the upazila education officers were

placed at the disposal of the upazilaparishad, a local council, and oversight of primary education

was transferred to local governments. The upazila parishad was also given the responsibility of

recruiting teachers in addition to the supervision of school management and development activities.

Subsequently, however, the authority to recruit teachers was taken away in response to agitation

by teachers and alleged malpractices in the recruitment process. In 1991, with the change in central

Government, the local government at the upazila level was abolished. The Government enacted

a new law bringing back local government at the upazila level, but the upazila elections had not

yet been held at the time of the preparation of this working paper.

The rapid expansion of primary schooling following the enactment of compulsory primary

education in 1991 was facilitated by a decentralized approach to school expansion. The Governmentallowed communities to set up schools to cater to the increase in demand for primary schooling.

Consequently, the number of nongovernment schools surged from 12,000 to 26,000 between 1991

to 1998, while the number of government schools remained unchanged at 38,000.

For secondary education, the Government controls nongovernment schools by linking

government subvention to adoption of national curriculum and textbooks. Management of

nongovernment schools, however, remains largely decentralized. The SMCs of these schools have

absolute authority in hiring teachers, subject to government regulations, but their authority to

fire staff is limited because such cases have to be referred to the Boards of Intermediate and

Secondary Education.

2. Draft National Education Policy, 1998

Decentralization is among the measures that were proposed in the Draft National Education

Policy, 1998 to improve the quality of education. The proposals include the complete decentralization

of the management of primary education. The Draft Policy recommended granting additional

authority to SMCs, formation of PTAs and involving them in school activities, lodging the internal

supervision of each school primarily with the principal, and strengthening and decentralizing

external supervision and monitoring by, for example, limiting the number of schools to be supervised

and monitored by each official at a realistic level. The proposals also include the decentralization

of secondary education up to upazila level. The Draft Policy recommended that SMCs should be

strengthened by giving them more authority and stressed the need for supervision by societyinvolving guardians, local people interested in promoting education, leaders, and the local

government. For academic supervision and monitoring, it proposed the creation of adequate posts

of inspectors so that each school is thoroughly inspected at least once a quarter.



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G. Assessing the Impact of Decentralization in Bangladesh

To assess the impact of some aspects of decentralization, a mini-survey was carried out

among 205 schools as part of this project. These schools included 92 government primary schools,

18 government secondary schools, and 95 nongovernment secondary schools. Schools were drawn

from both urban and rural areas of two regionsDhaka and Kushtia-Rajbari-Faridpur (KRF).

The individual schools were selected at random from among those accessible with relative ease

from the point of view of the investigators (the schools left out however were not necessarily located

in remote areas). The survey was conducted over 2 months, from August to September 1999.

Principals of all schools (except one government school, due to his non-availability) were

interviewed for information relating to various aspects of the schools using structured

questionnaires. Their personal opinions on a number of issues were also recorded. Although there

were plans to interview the chairperson, and five nonteacher members from the SMCs of each

school, due to the non-availability of the persons concerned, it was not possible to conduct all the

interviews. About five teachers and five guardians of students of each school were also interviewed.Finally, a standard 30-minute test to ascertain academic achievements was conducted for about

30 students studying in Class V of primary schools and Class VIII of secondary schools.

The aspect of education decentralization about which there is the most information and

most experience in Bangladesh is school-based management (SBM). SBM has been in practice

for a long time in nongovernment secondary schools, with SMCs running the schools. SMCs have

also been instituted in all primary schools to increase community participation in managing and

financing education.

The Bangladesh country study analyzed the survey it conduced and information gathered

from several focus group discussion meetings with concerned people held both inside and outside

Dhaka to assess the impact of SMCs in shaping education outcomes and their determinants. The

analysis is based on cross-tabulations, which of course do not permit control for many factors that

could affect the variables of concern.

1. Findings of the Survey: Mean Student Achievement Scores

Table 4 presents mean student achievement test scores by school types and geographic

areas.

a. Primary Schools

The low quality of primary schooling is reflected in the test scores of students sampled.

The overall score for the three subjects averaged 29 percent, which is less than the standard passmark of 33 percent. English scores are the worst, at 11 percent. There is little difference in the

overall score between the two regions but rural-urban differences are substantial notably in the

Dhaka region, where the average score of urban schools is 7 percent compared with 50 percent

in rural schools (Figure 2). In contrast, in the KRF region the difference was insignificant29

percent in rural areas compared with 28 percent in urban areas.


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Table 4.Average Student Achievement Test Scores by School Type,Rural-Urban Distribution, and Regional Distribution

No. of Test Scores (Percent)Schools Bengali English Math Total

Government Primary SchoolsAll Regions 92 36 11 40 29

Rural 56 46 16 60 40Urban 36 21 2 8 10

Dhaka Region 61 36 9 40 28Rural 30 54 18 79 50Urban 31 18 1 3 7

Kushtia-Rajbari-Faridpur Region 31 37 12 37 29Rural 26 37 13 37 29Urban 5 38 6 39 28

Government Secondary SchoolsAll Regions 18 33 37 50 40Dhaka Region 10 28 36 46 37Kushtia-Rajbari-Faridpur Region 8 39 39 55 44

Nongovernment Secondary SchoolsAll Regions 95 30 25 35 31

Rural 58 34 27 42 35Urban 37 25 21 25 24

Dhaka Region 56 27 24 30 27Rural 26 33 28 40 34Urban 30 22 21 21 22

Kushtia-Rajbari-Faridpur Region 39 35 25 43 35Rural 32 35 26 43 35Urban 7 38 22 44 35


Figure 2.Average Student Achievement Test Scores (%)in Government Primary Schools, by Region and Subject,

Bangladesh

Urban Rural

Dhaka Region Kushtia-Rajbari-Faridpur Region

50

40

30

20

10

0

7

50

28 29


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b. Secondary Schools

Students in government schools performed relatively better (40 percent) than students

in nongovernment schools (31 percent). Both government and nongovernment schools performed

better in the KRF region than in the Dhaka region (Figure 3). In the Dhaka region, rural

nongovernment secondary schools, in general, performed better than their urban counterparts

even though a few urban schools performed reasonably well. In the KRF region, on the other hand,

there is no difference between urban and rural schools, with both averaging 35 percent.

2. Correlates of Mean School Achievement Scores

The survey solicited responses on a wide range of variables that are usually associated

with schooling outcomes and are often interpreted to have causal effects on schooling outcomes.

These can be grouped into four broad categories:

(i) the quality of education services provided by the school, which is a function ofphysical inputs such as availability of adequately well-furnished and spacious

classrooms; library and laboratory facilities; availability of well-qualified, well-

trained, and highly motivated teachers discharging their duties in a planned and

organized manner; a scientific and relevant curriculum; and adequate supply of

necessary teaching and learning aids;

45

40

35

30

25

20

Dhaka Region Kushtia-Rajbari-Faridpur

Government Nongovernment

37

27

44

35

Figure 3.Average Student Test Scores (%) in Government

and Nongovernment Secondary Schools, by Region, Bangladesh


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(ii) students involvement in education through regular attendance at schools, effective

participation in various school activities, and study at home;

(iii) home environment and role of parents or other guardians; and

(iv) school management.

The results are summarized in the following paragraphs.

a. Primary Schools

(i) Rural primary schools were better housed, i.e., were housed in buildings, compared

with their urban counterparts. Only 14 percent of urban primary schools were housed

in buildings compared with 87 percent of rural primary schools. In Dhaka City none

of the schools surveyed were housed in buildings. The majority of rural schools,

however, did not have adequate accommodation for all students enrolled and their

classrooms were poorly furnished. Facilities such as electricity connections andlibraries were better in urban schools than in rural schools.

(ii) Both rural and urban schools reported shortages of teachers with the situation more

severe in urban areas. However, primary schoolteachers in urban areas on average

have higher qualifications than those in rural schools, even though the proportion

of teachers with formal teacher training is higher in rural areas than in urban areas.

(iii) Attendance of primary school students in their respective classes, on the day of

the survey, ranged between 60 percent and 74 percent in most of the schools. The

urban schools, particularly those belonging to Dhaka City, had the lowest attendance.

(iv) Of principals of rural primary schools, 82 percent felt that their teachers lacked

aptitude, motivation, and adequate knowledge in the subjects that they were

teaching. On the other hand, principals ofall urban primary schools reported the

same.

(v) In most rural primary schools, the principals had HSC as their highest academic

attainment, and very few had training in education beyond primary training

institute.

(vi) All the rural primary schools had regular and duly constituted SMCs whereas only

about four fifths of the urban primary schools surveyed had regular and duly

constituted SMCs. Principals in rural schools had more positive responses to the

role of their SMCs in the area of ensuring regular and timely attendance of teachers,

implementation of co-curricular activities, and monitoring of repair of school

infrastructure and furniture, etc. SMCs in urban schools did not seem to have madesignificant contributions at all.

(vii) Most of the rural primary schools, 56 out of 60, had PTAs compared with only 16

out of 36 urban primary schools. But the majority of PTAs were inactive and few

principals responded that the performance of PTAs was satisfactory.



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b. Secondary Schools

(i) All government secondary schools were properly housed while a wide variation in

facilities was noticed among nongovernment secondary schools. Most secondary

schools lacked adequate accommodation and furniture for all their enrolled students,

but government schools were a little better off compared with nongovernment

schools, and among nongovernment schools, urban schools enjoyed better facilities

than rural counterparts. Most of the schools had adequate supplies of standard

teaching aids.

(ii) Government secondary schools had a comparatively better-educated teaching staff.

Within the nongovernment sector, the urban schools had a better-educated teaching

staff compared with their rural counterparts. While 86 percent of teachers of

government secondary schools received some form of training in education, the

percentage of teachers of nongovernment schools receiving training was 59 percent

for rural schools and 72 percent for urban schools.(iii) Attendance of students was generally poor. Nearly half the nongovernment

secondary schools for boys had less than 60 percent attendance on the day the survey

was conducted. In government schools attendance was slightly better, ranging

between 60 and 74 percent.

(iv) Most of the principals expressed poor opinions about their colleagues knowledge

in the specific subjects that they taught, as well as their aptitude and motivation.

Principals of only four government and 20 nongovernment secondary schools

considered their school curriculum appropriate.

(v) The principals of government schools were relatively better educated on average

than principals of nongovernment schools. Principals of urban nongovernment

schools, however, were best educated, with some even having research degrees.

A similar picture emerges in terms of the level of training received by principals.

(vi) Most principals of government secondary schools felt that they were adequately

empowered by government regulations with respect to the enrollment of students,

selection of teachers for training, disciplining teachers and students, fixing co-

curricular activities, and preparation and implementation of academic programs.

In the case of nongovernment schools, principals perceptions in respect of what

they could and could not do as per government regulations varied widely. However,

most of the principals felt seriously constrained (even more so in rural schools) in

exercising the authority that they considered they had.

(vii) Most of the nongovernment secondary schools had SMCs. SMCs outside Dhakaappear to be properly constituted, each having a chairman and vice chairman but

this is not so in the Dhaka region. SMCs operating outside Dhaka also seemed to

be more active. All SMCs performed their tasks quite well, based on feedback from

principals, in terms of recruitment and administration of teachers.


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(viii) Only one government school reported having a PTA; the vast majority of nongov-

ernment schools did not have a PTA. Very few PTAs were active.

3. Relating Schooling Achievement Scores to Decentralization

In an exercise such as this, it is impossible to draw confident conclusions about relationships

between the degree of decentralization and schooling outcomes. The survey found that government

secondary schools had higher test scores than nongovernment secondary schools. This does not

necessarily confirm any relationship with the degree of autonomy of schools. Because government

secondary schools, which are located mostly in urban areas, have reasonably good physical

infrastructure and other classroom facilities, and more qualified and trained teachers, it is not

surprising that student scores are also better. More important, government schools may, for a

variety reasons, attract better students. It should also be noted that government secondary schools,

while managed by a highly centralized education bureaucracy, in actual fact enjoy considerable

autonomy because of the shortage of human resources in DSHE.What the survey has done is to provide useful insights into the current system of

management of schools and especially the role of SMCs that may provide some indication of the

potential role that further decentralization of the education sector can play in improving the quality

of schooling in Bangladesh.

Nongovernment secondary schools, though managed by the community through their

participation in SMCs that exercise considerable power and authority, appear to have failed to

fully exploit the advantages of decentralization for a variety of reasons (given below). The insights

are provided by interviews of chairpersons and nonteacher members of SMCs of schools covered

by the survey.

The quality of the membership and leadership of SMCs is generally poor, particularly among

urban primary schools in the Dhaka region. There is a general lack of awareness about their duties

and responsibilities, and their commitment. Quite often they meddle in internal affairs of the schools,

making the principals ineffective in discharging their duties, which not only adversely affects the

schooling outcomes, but also vitiate the overall academic environment of the schools. In schools

where SMCs are properly constituted, remain active, and extend the necessary support to the

principal, schooling outcomes are generallysatisfactory. In nongovernment secondary schools outside

Dhaka City, SMCs are properly constituted, function relatively better, and as the test scores indicate,

produce better schooling outcomes than schools in Dhaka City.

In the case of primary schools, SMCs have little role to play because the education

bureaucracy, through its elaborate administrative network, has firm control over all government

primary schools. As a result, SMCs have failed to attract adequate community participation.

H. Implications

Despite the qualifications noted above, Masum (2000) concludes that there is a need to

ensure greater autonomy of government schools. For government primary schools, the existing

Section IIIBangladesh


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control by the education bureaucracy should be relaxed. Schoolteachers should be allowed to function

as teachers, rather than as petty government officials in a strict bureaucratic hierarchy as at present,

similar to teachers in government secondary schools. In the case of government secondary schools,

principals should be given some authority to fill vacant teaching positions with appropriately

qualified teachers with the required expertise, perhaps from a panel of teachers already selected

by DSHE, and some authority in fixing school fees on the basis of the income of guardians. In

the case of nongovernment secondary schools, the SMCs need to be constituted and their roles

defined so that they serve essentially as supporting institutions, with full executive authority for

running the schools vested with the principal. The Government further should establish one

government secondary school in every upazila to serve as a model for nongovernment secondary

schools.

III. INDONESIA14

Until the eruption of the Asian financial crisis, Indonesia had been viewed by many as amodel country that, along with rapid economic growth, had made impressive achievements in the

education sector. Gross enrollments in primary schools increased from 62 percent in 1973 to 101

percent in 1983; junior secondary school enrollments increased from 18 percent in the early 1970s

to 70 percent in 1997. In 1994 senior secondary and tertiary enrollments reached 35 and 17 percent

respectively. The improvement in the gender (female/male) ratio at all levels of education is also

another indicator often cited as evidence of Indonesias achievements. By the mid-1990s, the gender

ratio for primary enrollment had risen to 93 percent while the gender ratio at the senior secondary

level had reached 88 percent, compared with 50 percent in the mid-1970s. Preserving these gains

has hence been a priority of the Indonesian Government since the financial crisis broke out.

promoting effective schooling through education decentralization in bangladesh, indonesia, and...

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